Records: show longest dry streak instead of record-low precipitation (#105)

Record-low rainfall is meaningless (always ~0), so the precip row's low side now
shows the longest run of consecutive days without measurable rain and the date that
dry spell began (grading.longest_dry_streak), keeping the wettest day on the high
side. A footnote explains the substitution.

content.py

@@ -347,10 +347,18 @@ def _records_context(request, city, history) -> dict:
         r = rec.get(key)
         if not r:
             continue
+        if key == "precip":
+            # "Record low" rain is meaningless (it's just 0), so the low side shows
+            # the longest dry streak and the date it began instead.
+            days, dry_start = grading.longest_dry_streak(history)
+            low = f"{days}-day dry spell" if days else "—"
+            low_date = dry_start or "—"
+        else:
+            low, low_date = _fmt(key, r["min"]), r["min_date"]
         rows.append({
             "label": label,
             "high": _fmt(key, r["max"]), "high_date": r["max_date"],
-            "low": _fmt(key, r["min"]), "low_date": r["min_date"],
+            "low": low, "low_date": low_date,
         })
     breadcrumb = [("Home", f"{BASE}/"), ("Climate", f"{BASE}/climate"),
                   (name, f"{BASE}/climate/{city['slug']}"), ("Records", None)]

grading.py

@@ -182,6 +182,30 @@ def all_time_records(df: pl.DataFrame) -> dict:
     return out
 
 
+def longest_dry_streak(df: pl.DataFrame) -> tuple[int, str | None]:
+    """Longest run of consecutive days without measurable rain, and the ISO date the
+    streak began. A dry day is precip < RAIN_THRESHOLD; null precip counts as dry."""
+    if "precip" not in df.columns:
+        return (0, None)
+    d = df.select(["date", "precip"]).sort("date")
+    dates, precips = d["date"].to_list(), d["precip"].to_list()
+    best_len, best_start = 0, None
+    cur_len, cur_start = 0, None
+    for dt, p in zip(dates, precips):
+        wet = p is not None and not (isinstance(p, float) and np.isnan(p)) and p >= RAIN_THRESHOLD
+        if wet:
+            cur_len, cur_start = 0, None
+        else:
+            if cur_len == 0:
+                cur_start = dt
+            cur_len += 1
+            if cur_len > best_len:
+                best_len, best_start = cur_len, cur_start
+    start = best_start.isoformat() if best_start and hasattr(best_start, "isoformat") else (
+        str(best_start) if best_start else None)
+    return (best_len, start)
+
+
 def _band_stats(samples: np.ndarray) -> dict | None:
     if samples.size == 0:
         return None

templates/records.html.j2

@@ -26,6 +26,9 @@
       </tbody>
     </table>
   </div>
+  <p class="records-note muted">Rainfall has no meaningful record low, so its “record low”
+     column shows the <b>longest run of consecutive days without measurable rain</b> and the
+     date that dry spell began.</p>
 
   <p><a class="cta" href="{{ base }}/#{{ '%.5f,%.5f' | format(city.lat, city.lon) }}">Grade {{ name }}'s weather now →</a></p>
   <p class="climate-foot muted"><a href="{{ base }}/climate/{{ city.slug }}">‹ Back to {{ name }} climate</a></p>